Employing Ideomotor Theory as the basis of a Robot Tutoring System

One way in which a robotic system might be considered ´intelligent´ may be an ability to learn and then generalise its learnt abilities in situations not previously encountered. Thus the ability to learn may be a prerequisite in allowing a robot to be adaptable when coping with changing environments, be useful when dealing with changing user requirements and expectations as well as being in itself a mechanism which supports the idea of intelligence and intelligent behaviour. One of the aims of the robotics research presented here is to study adaptive mechanisms which support learning with a focus on supervised learning via the interaction between a human teacher and a robot learner [6]. This interaction is based upon learning via imitation from observation of others as well as self-imitation, where the learner learns by reproducing actions it has perceived from another manipulating its body in order to highlight affordances and effectivities available for action [7]. In this talk I will suggest that the psychological notion of ´ideomotor theory´ may be a good starting point from which to construct adaptable robots which support learning from imitation. In doing this I will explain the ideas behind ideomotor theory, ranging from the initial work of Lotze [3] and James [2] to more recent research by Prinz [5] where the theory is extended to support imitation. I will contrast and compare ideomotor theory with other prevailing theories of imitation, such as Active intermodal matching [4] and Associative Sequence Learning [1] and suggest that the ideomotor approach may have more to offer the roboticist in conceiving learning systems. Finally I will demonstrate how these ideas can be put into practise with some examples of scaffolded teaching used to teach physical robots an object following task.